Full-Time Data Scientist

Key Areas of Focus:

Understanding in depth both the business and technical problems Dataworks aims to solve

Exploring data and crafting models to answer core business problems that may not have a common blueprint

Leading the invention of new approaches and algorithms for tackling data intensive problems

Pioneering R&D efforts to rapidly understand and assimilate state of the art methods

Scaling up from laptop-scale" to cluster scale" problems by leading efforts to standardize and industrialize solutions

Delivering tangible value very rapidly, collaborating with diverse teams of varying disciplines

Interacting with senior technologists from the broader enterprise and outside of FedEx (partner ecosystems and customers) to create synergies and identify opportunities for improvement

Codifying best practices for future reuse in the form of accessible, reusable patterns, templates, and code bases

Skills/Abilities:

You should have strong knowledge of optimization techniques such as Linear Programming and Integer Programming.

Technical background in computer science, data science, machine learning, artificial intelligence, statistics or other quantitative and computational science

A compelling track record of Data Science / Engineer expertise, designing and deploying large scale technical solutions, which deliver tangible, ongoing value

Direct experience having built and deployed robust, complex production systems through Cloud technologies that implement modern, data scientific methods at scale

Ability to context-switch, to provide support to dispersed teams which may need an expert hacker" to unblock an especially challenging technical obstacle

Demonstrated ability to deliver technical projects with a team, often working under tight time constraints to deliver value

An 'engineering' mindset, willing to make rapid, pragmatic decisions to improve performance, accelerate progress or magnify impact

Ability to work with distributed teams on code-based deliverables using version control

Solid theoretical grounding in the mathematical core of the major ideas in data science

Expert level understanding of a class of modelling or analytical techniques, often supported by Masters- or Doctoral-level research in the subject

Deep fluency in the mathematical 'primitives' and generalizations of data science - e.g., expertise in Linear Algebra, and Vector Calculus

Use of agile and devops practices for project and software management including CI/CD; process improvement and quality management experience (e.g., Lean, Six Sigma, QDM expert)

Demonstrated expertise in working with some of the following common languages and tools:

SKLearn, XGBoost, Tensorflow, Pytorch, MLlib and other core ML frameworks

Python, Scala, R, C++, Java and other modern programming languages

MLFlow, Databricks, Spark, Kafka, Hive, Hadoop and other data tools and frameworks

CPLEX, Gurobi and other similar optimization modeling packages

Minimum qualifications:

Master's Degree or equivalent in computer science, operations research, statistics, applied mathematics or related quantitative discipline. Two (2) years' work experience in applying data science (machine learning, artificial intelligence, statistical analysis), operations research (optimization, algorithms, mathematical modeling), and data analytics modeling to decrease cost, increase profitability, and improve customer experience. Knowledge and general awareness of data science and machine learning tools and methods, including the iterative development of analysis pipelines to provide insights at scale. Familiarity with conducting end-to end analyses, including data gathering and requirements specification, processing, analysis, and presentations. General understanding of the transportation industry, competitors, and evolving technologies. Experience as a member of multi-functional project teams. Strong oral and written communication skills.

Pay Transparency: This compensation range is provided as a reasonable estimate of the current starting salary range for this role across all potential locations. If this opportunity includes multiple job levels, the salary information represents the job level minimum and the job level maximum. Actual starting pay would be determined by experience relative to the job, market level, pay at the location for this job and other job-related factors permitted by law. An employee may be eligible for additional pay, premiums, or bonus potential. The Company offers eligible employees health, vision and dental insurance, retirement, and tuition reimbursement.

Domicile Information:

This position can be domiciled anywhere in the United States. The ability to work remotely within the United States may be available based on business need.

Application Criteria:

Upload current copy of Resume (Microsoft Word or PDF format only) and answer job screening questionnaire by 09/06/24.